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From 1637 tulips to the AI supercycle, an evidence-first walk through the great speculative bubbles: what actually happened in each, what the legend gets wrong, and the four mechanics that repeat.
Ten bubbles, in order, from 1637 tulips to the AI supercycle. Each chapter is the evidence-first version, not the legend, and each one maps to the same four mechanics that keep repeating.
In 1637 a single Dutch tulip bulb could change hands for the price of an Amsterdam canal house, then the market fell roughly 99% in a week. What actually happened is more useful than the legend.
South Sea shares ran from about 128 pounds in January 1720 to roughly 1,000 by August, then crashed to 100-200 by December. The real business was never trade. It was converting the national debt.
In 1846 Parliament passed 272 railway acts and authorised capital near Britain's entire annual GDP. Most of those lines lost half their value or were never built. Real does not mean safe.
The Dow ran from about 63 in 1921 to 381 in September 1929, then fell roughly 89% by 1932. The crash was real. The thing that turned it into a decade was the policy response, not the selloff.
In 1972 about fifty 'buy and never sell' growth stocks traded at 50 to 90x earnings, some above 100x. Then the 1973-74 bear market cut the S&P roughly 48% and many of them 60 to 90%. The companies were excellent. The price was the bubble.
On 19 October 1987 the Dow fell 22.6% in a single day, the biggest one-day drop ever. No recession followed. The reason was code, and the response was a Fed that printed before lunch.
The Nasdaq ran from about 1,000 in 1996 to 5,048 in March 2000, then fell roughly 78% and erased about 5 trillion dollars. The trend was right. Picking the survivor was the hard part.
The S&P 500 fell about 57% from its 2007 peak and Lehman filed the largest bankruptcy in US history. The shiny asset was houses. The real bubble was leverage, repriced AAA, and one model assumption.
GameStop hit roughly $483, Bitcoin roughly $69,000, ARKK and SPACs fell 67% or more in 2022, and bonds had their worst year in modern history. The single asset everyone missed was the one priced at zero: interest rates.
Hyperscalers are spending hundreds of billions a year on AI compute while the dominant chipmaker helps finance its own customers. The history of bubbles says real technology and a real bubble are not opposites.
Standalone explainers on the methods behind the research: the concepts you need before the charts make sense.
Walk-forward validation separates in-sample fluke from real edge. 104 (strategy, ticker) pairs tested on the QA universe - 56 ROBUST, 20 STABLE, 18 LUMPY, 10 no-trades. Here's the procedure, the verdicts, and why most retail backtests quietly fail it.
Mean reversion is a class, not a strategy. We walk-forwarded three implementations across 35 thematic names: regression-channel wins 22 of 35, Fibonacci basket wins at PF 1.76, flat-mean Bollinger wins 1 of 35. The structural reason is which mean you assume.
Textbook Fibonacci is 23.6 / 38.2 / 50 / 61.8 / 78.6%. We backtested 48 user-curated levels across 12 themes - basket PF 1.76, Sharpe 1.42, +23.7% over 3 years. Here's what works, what doesn't, and on which name classes.
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